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DeepSeek V3 vs V4 Pro: Complete Comparison Guide

DeepSeek V3 DeepSeek V4 Comparison Pricing
Published: June 25, 2026 · Updated: June 25, 2026

With multiple DeepSeek model variants available — V3, V3.1, V3.2, V4 Pro, V4 Flash, and R1 — choosing the right model for your project can be confusing. Here is what actually differs between them: architecture, price per million tokens, measured performance and the workloads each one suits.

DeepSeek Model Family Overview

Model Generation Context Best For Status
DeepSeek V4 Pro 4th gen (latest) 128K Best all-round performance ✅ Recommended
DeepSeek V4 Flash 4th gen 128K Fast, affordable inference ✅ Recommended
DeepSeek R1 (Reasoner) 4th gen 128K Chain-of-thought reasoning ✅ Recommended
DeepSeek V3 3rd gen 64K Legacy applications ⚠️ Being phased out
DeepSeek V3.1 3rd gen (refined) 64K Incremental V3 update ⚠️ Legacy
DeepSeek V3.2 3rd gen (refined) 64K Minor V3 improvement ⚠️ Legacy
ERNIE 4.0 (Baidu)$0.55$0.55128K

Pricing Comparison

Model Input (per 1M tokens) Output (per 1M tokens) Cost vs V4 Pro
DeepSeek V4 Pro $0.14 $0.28 — (baseline)
DeepSeek V4 Flash $0.07 $0.14 🏆 50% cheaper
DeepSeek R1 $0.55 $1.10 3.9x more
DeepSeek V3 $0.27 $1.10 1.9x more
GPT-4o (for reference) $2.50 $10.00 17.9x more
ERNIE 4.0 (Baidu)$0.55$0.55128K

💡 Key finding: DeepSeek V4 Pro is nearly half the price of DeepSeek V3 ($0.14 vs $0.27/1M input) while delivering significantly better performance. There is no cost advantage to staying on V3.

Architecture & Performance

DeepSeek V3 Architecture

DeepSeek V3 uses a Mixture-of-Experts (MoE) architecture with 671B total parameters and 37B activated per token. It features a 64K context window, Multi-head Latent Attention (MLA), and was trained on 14.8T tokens. V3.1 and V3.2 are incremental refinements with minor alignment and safety improvements but share the same core architecture.

DeepSeek V4 Architecture

DeepSeek V4 represents a major architectural leap. Built on an improved MoE design with enhanced attention mechanisms, V4 Pro achieves significant gains in reasoning, coding, and multilingual performance while reducing inference costs. The 128K context window doubles V3's capacity.

Performance Benchmarks

BenchmarkDeepSeek V4 ProDeepSeek V3Improvement
MMLU (knowledge)90.2%86.8%+3.4%
HumanEval (coding)92.5%85.4%+7.1%
MATH (reasoning)88.7%79.2%+9.5%
Context Length128K64K+100%
Inference Speed~40% fasterBaseline+40%
ERNIE 4.0 (Baidu)$0.55$0.55128K

V3 vs V4: Which Should You Choose?

Choose DeepSeek V4 Pro if you need:

Stick with DeepSeek V3 only if:

Consider DeepSeek V4 Flash for cost-sensitive workloads:

What About V3.1 and V3.2?

DeepSeek V3.1 and V3.2 are minor updates to the V3 base model with alignment improvements, better instruction following, and safety updates. They do not introduce architectural changes and their performance is broadly similar to V3. For most users, upgrading directly from V3/V3.1/V3.2 to V4 Pro offers the best return on investment.

DeepSeek R1: The Reasoning Specialist

DeepSeek R1 (DeepSeek Reasoner) is a chain-of-thought reasoning model designed for complex multi-step problems. While V4 Pro handles most tasks efficiently, R1 excels at:

At $0.55/1M input tokens, R1 is more expensive than V4 Pro but justified for tasks that require deep reasoning.

Quick Reference: When to Use Each Model

Use Case Recommended Model Rationale
General chatbot / assistant DeepSeek V4 Pro Best balance of quality and cost
High-volume production API DeepSeek V4 Flash most cost-effective option at $0.07/M
Complex math / logic problems DeepSeek R1 Chain-of-thought reasoning
Code generation & review DeepSeek V4 Pro Top coding performance (+7.1%)
Long document processing DeepSeek V4 Pro or Kimi K2.5 128K or 200K context window
Legacy V3 migration DeepSeek V4 Pro Drop-in upgrade, lower price
ERNIE 4.0 (Baidu)$0.55$0.55128K

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Frequently Asked Questions

Is DeepSeek V4 better than V3?

Yes. DeepSeek V4 Pro outperforms V3 across all benchmarks — especially coding (+7.1%), reasoning (+9.5%), and knowledge (+3.4%) — while being nearly half the price. The upgraded architecture also supports 128K context (up from 64K) and delivers ~40% faster inference.

Is DeepSeek V4 cheaper than V3?

Yes. V4 Pro costs $0.14/1M input tokens compared to V3's $0.27/1M — almost half the price for better performance. V4 Flash is even cheaper at $0.07/1M. There's no cost incentive to stay on V3.

What happened to DeepSeek V3.1 and V3.2?

V3.1 and V3.2 were minor refinements of the V3 base with alignment and safety improvements. They don't change the architecture or core performance. Users on any V3 variant should upgrade to V4 Pro.

What's the difference between DeepSeek V4 Pro and V4 Flash?

V4 Pro is the full flagship model with maximum performance. V4 Flash is a distilled variant optimized for speed and cost — half the price of Pro ($0.07 vs $0.14) with slightly lower but still strong quality.

How does DeepSeek R1 compare to V4 Pro?

R1 (Reasoner) excels at chain-of-thought reasoning but is more expensive ($0.55 vs $0.14/1M input). Use V4 Pro for general tasks and R1 specifically when you need step-by-step logical reasoning for complex problems.

What context window does each DeepSeek model support?

DeepSeek V4 Pro and V4 Flash support 128K tokens. DeepSeek R1 supports 128K tokens. DeepSeek V3 and all its variants (V3.1, V3.2) support 64K tokens.

References

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